SOM Biotech, a clinical-stage biopharmaceutical company with AI-based drug discovery technology and a focus on neurological orphan diseases, announces it has signed a licensing agreement with the University of Minnesota.
This license agreement follows the completion of research under a sponsored research agreement (SRA) signed in 2019, in which the University of Minnesota conducted a series of in vitro studies on potential pre-clinical product candidates for Duchenne and Becker muscular dystrophy identified using SOM Biotech’s exclusive platform, SOMAIPRO. The work under the SRA resulted in inventions covering nine potential product candidates, which SOM chose to license exclusively from the University of Minnesota.
SOM is currently conducting additional preclinical studies at the University of Minnesota to select the best potential candidates to take forward into development for Duchenne and Becker muscular dystrophy. The project was performed with the support of the Duchenne Parent Project Spain.
Raúl Insa, chief executive officer of SOM Biotech, said: “This agreement with the University of Minnesota, a leading global research university, shows the exceptional value provided by our SOMAIPRO platform and its unique approach to AI-based drug discovery. The research that has already been conducted by the University of Minnesota is very encouraging and we are looking forward to continuing that at SOM Biotech in order to bring innovative potential treatments to patients with high unmet medical needs.”
SOM Biotech successfully uses SOMAIPRO to identify drugs effective for the treatment of a specific disease, to discover new mechanisms of action and new applications for a drug, and to predict the toxicity of the compounds, as well as the molecular scaffolds for compounds active on a given target. While other AI-based approaches use methods based on data mining, structural similarity, or the target structure, SOMAIPRO uses molecular fields, allowing for an increased rate of success, with results achieved in the shortest possible time and considerably reducing the costs associated with drug discovery.